Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example

Ranjeet Devarakonda; Giri Prakash; Kavya Guntupally; Jitendra Kumar

doi:10.1109/BigData47090.2019.9006051

Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example

Ranjeet Devarakonda, Giri Prakash, Kavya Guntupally, Jitendra Kumar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

Atmospheric Radiation Measurement (ARM) is a multi-laboratory/multi-institutional, US Department of Energy Office of Science National User Facility. ARM's data is currently hosted at the ARM Data Center (ADC) in Oak Ridge, Tennessee. The ADC holds more than 12,000 data products, with a total holding of more than 1.8 PB of data that dates back to 1992. This includes data from instruments, value-added products, model outputs, field campaigns, and principle investigator contributed data. In this paper, we discuss how big federal scientific data centers, such as ARM, that use modern and scalable architecture apply findable, accessible, interoperable, and reusable (FAIR) data principles to improve overall efficiency. These principles mainly emphasize machine-to-machine interactions that are directly applicable to ARM because of its data volume.

Original language	English
Title of host publication	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
Editors	Chaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6033-6036
Number of pages	4
ISBN (Electronic)	9781728108582
DOIs	https://doi.org/10.1109/BigData47090.2019.9006051
State	Published - Dec 2019
Event	2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States Duration: Dec 9 2019 → Dec 12 2019

Publication series

Name	Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference	2019 IEEE International Conference on Big Data, Big Data 2019
Country/Territory	United States
City	Los Angeles
Period	12/9/19 → 12/12/19

Funding

This research was supported by the Atmospheric Radiation Measurement (ARM) user facility, a U.S. Department of Energy (DOE) Office of Science user facility managed by the Office of Biological and Environmental Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/downloads/doe-public-access-plan).

Funders	Funder number
Office of Biological and Environmental Research
U.S. Department of Energy
Office of Science

Keywords

ARM Data Center
Big data
FAIR
data management
scientific data mining

Access to Document

10.1109/BigData47090.2019.9006051

Cite this

Devarakonda, R., Prakash, G., Guntupally, K., & Kumar, J. (2019). Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 (pp. 6033-6036). Article 9006051 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData47090.2019.9006051

Devarakonda, Ranjeet ; Prakash, Giri ; Guntupally, Kavya et al. / Big Federal Data Centers Implementing FAIR Data Principles : ARM Data Center Example. Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. editor / Chaitanya Baru ; Jun Huan ; Latifur Khan ; Xiaohua Tony Hu ; Ronay Ak ; Yuanyuan Tian ; Roger Barga ; Carlo Zaniolo ; Kisung Lee ; Yanfang Fanny Ye. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 6033-6036 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

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title = "Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example",

abstract = "Atmospheric Radiation Measurement (ARM) is a multi-laboratory/multi-institutional, US Department of Energy Office of Science National User Facility. ARM's data is currently hosted at the ARM Data Center (ADC) in Oak Ridge, Tennessee. The ADC holds more than 12,000 data products, with a total holding of more than 1.8 PB of data that dates back to 1992. This includes data from instruments, value-added products, model outputs, field campaigns, and principle investigator contributed data. In this paper, we discuss how big federal scientific data centers, such as ARM, that use modern and scalable architecture apply findable, accessible, interoperable, and reusable (FAIR) data principles to improve overall efficiency. These principles mainly emphasize machine-to-machine interactions that are directly applicable to ARM because of its data volume.",

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author = "Ranjeet Devarakonda and Giri Prakash and Kavya Guntupally and Jitendra Kumar",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Big Data, Big Data 2019 ; Conference date: 09-12-2019 Through 12-12-2019",

year = "2019",

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doi = "10.1109/BigData47090.2019.9006051",

language = "English",

series = "Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019",

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Devarakonda, R, Prakash, G, Guntupally, K & Kumar, J 2019, Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example. in C Baru, J Huan, L Khan, XT Hu, R Ak, Y Tian, R Barga, C Zaniolo, K Lee & YF Ye (eds), Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019., 9006051, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, Institute of Electrical and Electronics Engineers Inc., pp. 6033-6036, 2019 IEEE International Conference on Big Data, Big Data 2019, Los Angeles, United States, 12/9/19. https://doi.org/10.1109/BigData47090.2019.9006051

Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example. / Devarakonda, Ranjeet; Prakash, Giri; Guntupally, Kavya et al.
Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. ed. / Chaitanya Baru; Jun Huan; Latifur Khan; Xiaohua Tony Hu; Ronay Ak; Yuanyuan Tian; Roger Barga; Carlo Zaniolo; Kisung Lee; Yanfang Fanny Ye. Institute of Electrical and Electronics Engineers Inc., 2019. p. 6033-6036 9006051 (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T2 - 2019 IEEE International Conference on Big Data, Big Data 2019

AU - Devarakonda, Ranjeet

AU - Prakash, Giri

AU - Guntupally, Kavya

AU - Kumar, Jitendra

PY - 2019/12

Y1 - 2019/12

N2 - Atmospheric Radiation Measurement (ARM) is a multi-laboratory/multi-institutional, US Department of Energy Office of Science National User Facility. ARM's data is currently hosted at the ARM Data Center (ADC) in Oak Ridge, Tennessee. The ADC holds more than 12,000 data products, with a total holding of more than 1.8 PB of data that dates back to 1992. This includes data from instruments, value-added products, model outputs, field campaigns, and principle investigator contributed data. In this paper, we discuss how big federal scientific data centers, such as ARM, that use modern and scalable architecture apply findable, accessible, interoperable, and reusable (FAIR) data principles to improve overall efficiency. These principles mainly emphasize machine-to-machine interactions that are directly applicable to ARM because of its data volume.

AB - Atmospheric Radiation Measurement (ARM) is a multi-laboratory/multi-institutional, US Department of Energy Office of Science National User Facility. ARM's data is currently hosted at the ARM Data Center (ADC) in Oak Ridge, Tennessee. The ADC holds more than 12,000 data products, with a total holding of more than 1.8 PB of data that dates back to 1992. This includes data from instruments, value-added products, model outputs, field campaigns, and principle investigator contributed data. In this paper, we discuss how big federal scientific data centers, such as ARM, that use modern and scalable architecture apply findable, accessible, interoperable, and reusable (FAIR) data principles to improve overall efficiency. These principles mainly emphasize machine-to-machine interactions that are directly applicable to ARM because of its data volume.

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BT - Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

A2 - Baru, Chaitanya

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A2 - Zaniolo, Carlo

A2 - Lee, Kisung

A2 - Ye, Yanfang Fanny

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 9 December 2019 through 12 December 2019

ER -

Devarakonda R, Prakash G, Guntupally K, Kumar J. Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example. In Baru C, Huan J, Khan L, Hu XT, Ak R, Tian Y, Barga R, Zaniolo C, Lee K, Ye YF, editors, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 6033-6036. 9006051. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019). doi: 10.1109/BigData47090.2019.9006051

Big Federal Data Centers Implementing FAIR Data Principles: ARM Data Center Example

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